Paul Maxwell's PhD Thesis Abstract

Robust Resource Allocation Heuristics for Military Village Search Missions

Ph.D., Colorado State University, May 2012

Co-Major Professors: H. J. Siegel and Anthony A. Maciejewski

On the modern battlefield, cordon and search missions (a.k.a. village searches) are conducted daily. Creating resource allocations that assign different types of search teams (e.g., soldiers, robots, unmanned aerial vehicles, military working dogs) to target buildings of various sizes is difficult and time consuming in the static planning environment. Efficiently and effectively creating resource allocations when needed during mission execution (a dynamic environment) is even more challenging. There are currently no automated means to create these static and dynamic resource allocations for military use. Military planners create village search plans using reference tables in Field Manuals and personal experience. These manual methods are time consuming and the quality of the plans produced are unpredictable and not quantifiable. This work creates a mathematical model of the village search environment, and proposes static and dynamic resource allocation heuristics using robustness concepts. The result is a mission plan that is resilient against uncertainty in the environment and that saves valuable time for military planning staff.